CN110350522A - A kind of electric system vulnerable line identifying method based on Weighted H index - Google Patents
A kind of electric system vulnerable line identifying method based on Weighted H index Download PDFInfo
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- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
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- H—ELECTRICITY
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Abstract
The invention discloses a kind of electric system vulnerable line identifying methods based on Weighted H index, comprise the concrete steps that: 1, considering the topological structure feature and operating status characteristic of power system network, establish the second level correlation networks of electric system；2, the weight and node strength for considering side in correlation networks, improve classical H index index, obtain Weighted H index index；3, the Weighted H exponent pair transmission line of electricity obtained according to step 2 is ranked up, and completes the identification of vulnerable line.The present invention considers that correlation net improves classical H index index, the computer capacity of index is expanded into real number field from integer field, it can vulnerable line in more accurate identification system, the Weighted H index index that the present invention is mentioned simultaneously cannot be only used for the vulnerable line identification of electric power networks, it can also be used for as piping network, in the vulnerability analysis of other networks such as energy transportation network.
Description
Technical field
It is specifically a kind of based on Weighted H index the present invention relates to vulnerable line discrimination method in power grid vulnerability analysis
Electric system vulnerable line identifying method.
Background technique
In recent years, large-scale blackout happens occasionally.Although these accident occurrence frequencies are not high, each accident is without exception
Will cause disastrous effect to society.The Brazilian large-scale blackout that in March, 2018 occurs causes about a quarter
User's power-off.Since a bus breaker overload is tripped, sending end converter station loses AC power source, causes bi-pole protection block.Again plus
Itself grid structure of upper Brazilian power network is unreasonable, causes to be affected by the crucial alternating current-direct current channel in north orientation south, final to cause
Cascading failure.It can be seen that certain critical circuits in system from the accident process push wave played to the diffusion of scope of power outage and help
The effect of billows.Therefore, the generation of cascading failure can effectively be prevented and block by searching for these vulnerable lines, be pacified to power grid is improved
Full operation level has important value.
Domestic and foreign scholars have made very big effort in the identification or search work of electric system vulnerable line, and main achievement is big
Cause can be divided into two classes.The first kind is the POWER SYSTEM STATE analysis based on reductionism.Such side utilizes using Load flow calculation as core
Certainty or probabilistic method describe power grid cascading fault propagation process.In conjunction with entropy theory, theory of risk assessment and Monte Carlo
Simulation recognizes vulnerable line.The above method mainly consider the Line Flow under grid disturbance transfer and distribution character,
Node voltage offset, the disturbance of virtual injecting power, system lose load etc..Second class is the identification based on Complex Networks Theory
Method.Complex Networks Theory proposes many network properties (such as small world and uncalibrated visual servo characteristic) and element statistical property is (such as
Degree, betweenness, cluster coefficients etc.) analyze the dynamic behavior of network.In conjunction with the electrical characteristic of power grid, electrical distance, electrical Jie
Number, trend betweenness and power betweenness are put forward one after another for the vulnerable line in identification system.In addition, being based on K nuclear decomposition, structure
Hole is theoretical, PageRank algorithm discrimination method is put forward one after another again.The above method take full advantage of power grid physical attribute and
The characteristics such as the power transfer under static parameter and disturbance, can help power system staff to understand in time, grasp system
In weak link；But the generation of large-scale blackout, which is established, to be shifted and transmits in power grid key element post-fault system responding power
On the dynamic characteristic of capacity variation.Therefore, system power passes after the identification of vulnerable line needs further to consider electric network fault
Relativity problem between defeated variation characteristic and transmission of electricity branch.
Summary of the invention
In order to provide the power grid vulnerable line discrimination method of a kind of high accuracy and validity, it is based on Weighted H index index,
Consider that power transmission conversion correlation recognizes vulnerable line between transmission of electricity branch.
Therefore, the present invention provides a kind of electric system vulnerable line identifying method based on Weighted H index, specific steps
Are as follows:
Step 1: considering the topological structure feature and operating status characteristic of power system network, establish the two of electric system
Grade correlation networks, specific construction method are as follows:
1.1 calculate electric system benchmark trend, record the Capacity Margin M of each routej；
1.2 using N-1 Load flow calculation as foundation, successively cut-offs every branch in power grid, with caused by after branch breaking other
The power flow increment of branch is that side right obtains a power increment matrix Δ P；
1.3 to determine whether branch power out-of-limit, if nothing, is transferred to step 1.4；Otherwise, retain out-of-limit branch in matrix Δ P
Then corresponding element value cut-offs out-of-limit branch, again computing system trend, update power increment according to second of power flow increment
Matrix Δ P；
1.4 by each element in power increment matrix Δ P divided by the Capacity Margin of corresponding branch, obtain improved correlation
Property matrix R, specifically:
Wherein Δ rijIt indicates that route i's cut-offs the influence caused by route j, is calculated by following formula:
M in formulajIndicate the Capacity Margin of route j, Δ PijIndicate that the power increment after route i is cut-off to route j, n indicate
Route sum in system, in the case where not considering transmission line of electricity to itself affect, all diagonal elements are all provided in correlation matrix R
It is 0；Then using grid branch as node, the element in matrix R is side right value, constructs a new network, as electric system
Second level correlation networks.
Step 2: considering the weight and node strength on side in correlation networks, classical H index index is improved, is obtained
Weighted H index index defines Weighted H index, definition node Weighted H index using counterpart node intensity are as follows:
In formula, WHiIndicate the Weighted H index of node i,Operator, w are calculated for Weighted H indexijExpression is referred to by node i
To the side right value of node j, Sj|iIndicate intensity of the node j relative to node i, SjIndicate the intensity of node j, ΓiIt indicates by node i
The set of all of its neighbor node of direction, α, β indicate regulatory factor；WHiBigger node, corresponding branch are more fragile.
The Weighted H index W H of calculate node iiAlgorithm specifically:
2.1 initializing correlation networks parameter；
2.2 initialization node i Weighted H index values, enable WHi=0, then all of its neighbor node of calculate node i is opposite
Node strength；
2.3 sort all of its neighbor node counterpart node intensity of node i according to sequence from small to large, formation sequence S
={ S1|i,S2|i,…,SM|i, M is the quantity of sequence S；Counting side right value corresponding with sequence S is W={ wi1,wi2,…,wiM}；
Each value w in 2.4 couples of sequence Wik, all in the sequence of calculation to be greater than wikAnd SUMWk, then WHik=min { Sk|i,
SUMWk, traverse all w in sequence WikAfterwards, the Weighted H index W H of node ii=max { WHik|k∈M}。
Step 3: the Weighted H exponent pair transmission line of electricity obtained according to step 2 is ranked up, and completes the identification of vulnerable line.
Specifically: the Weighted H index of every route in calculate node system topology, to route according to Weighted H index size into
Row descending sort, so that it is determined that the vulnerable line (i.e. critical circuits) of electric system.
The beneficial effects of the present invention are:
(1) present invention in simultaneously consider power system network structural topology characteristic and operating status characteristic, with based on also
The POWER SYSTEM STATE analysis vulnerable line discrimination method of original opinion is compared, and has preferably identification accuracy and validity；
(2) present invention uses improved H index index, depth and range that vulnerable line influences has been fully considered, to electricity
The cascading failure dynamic characteristic of net, which has, more deeply portrays.
(3) present invention can inhibit cascading failure communication strategy to provide new thinking to instruct electric power networks to develop, finding,
It is of great significance for the planning and safe and stable operation of electric system.
Detailed description of the invention
Fig. 1 is the wiring of power grid physics and correlation networks mapping graph.
Fig. 2 is node A and its adjacent node schematic diagram.
Fig. 3 is node B and C and its adjacent node schematic diagram.
Fig. 4 is bidirectional weighting network topology structure figure.
Fig. 5 is route calculated attack flow chart.
Fig. 6 is IEEE39 node system figure.
Fig. 7 is Weighted H index figure compared with the indexing of the classics exponential region H.
Specific embodiment
With reference to the accompanying drawing, the present invention is further described in detail.
The present invention is based on Weighted H index indexs, provide a kind of electric system vulnerable line identifying side based on Weighted H index
Method considers that power transmission conversion correlation recognizes vulnerable line between transmission of electricity branch, and this method has sufficiently caught fragility
The depth and range of line influence have the cascading failure dynamic characteristic of power grid and more deeply portray.
Specific embodiment is as follows:
Step 1: the modeling of electric system second level correlation networks
The topological structure feature of power grid and the state characteristic of system operation are considered in order to balance, are based on second level cascading failure,
The construction method that electric system proposes second level correlation networks is established, specifically:
1.1 computing system benchmark trends, record the Capacity Margin M of each routej；
1.2 using N-1 Load flow calculation as foundation, successively cut-offs every branch in power grid, with caused by after branch breaking other
The power flow increment of branch is that side right obtains a power increment matrix Δ P；
1.3 to determine whether branch power out-of-limit, if nothing, is transferred to step 1.4；Otherwise, retain out-of-limit branch in matrix Δ P
Then corresponding element value cut-offs out-of-limit branch, again computing system trend, update power increment according to second of power flow increment
Matrix Δ P；
1.4 by each element in power increment matrix Δ P divided by the Capacity Margin of corresponding branch, obtain improved correlation
Property matrix R, specifically:
Wherein Δ rijIt indicates that route i's cut-offs the influence caused by route j, is calculated by following formula:
M in formulajIndicate the Capacity Margin of route j, Δ PijIndicate that the power increment after route i is cut-off to route j, n indicate
Route sum in system, in the case where not considering transmission line of electricity to itself affect, all diagonal elements are all provided in correlation matrix R
It is 0；Then using grid branch as node, the element in matrix R is side right value, constructs a new network, as former power grid
Second level correlation networks.
For second level correlation networks for subsequent fragile transmission line of electricity identification, establishment process is as shown in Figure 1.
Step 2: classical H index index being improved, Weighted H index index is obtained.
Classical H index is to be proposed by Jorge Hirsch in 2005, and the purpose is to quantify scientific research personnel as independent
The research achievement of individual, is widely applied in academia.Its original definition is that the H index of a scientist refers to its hair
There is h every to be at least cited h times in the Np piece paper of table and remaining Np-h paper every is drawn respectively less than h times.
From the point of view of complex network, H index can recognize the influence power for having no right nodes.As shown in Fig. 2, node
A has 4 adjacent nodes, and node strength is respectively 2,3,4 and 5.So, node A has 4 adjacent node intensity >=2, there is 3
Adjacent node intensity >=3, but without 4 adjacent node intensity >=4, according to the definition of H index, HA=3.
In fact, real-life network is mostly weighted network, different side right values assume responsibility for different effect and
Function, and side right value is not necessarily all integer.It is classical when the concept of H index is expanded in the correlation networks established herein
H index only only account for the influence of adjacent node, have ignored the importance of side right value, and its calculated result is integer,
Calculated result discrimination is obviously little.The H index of situation as shown in Figure 3, node B and C is all 3, can not compare two nodes
Influence power.Therefore, this patent proposes to consider the Weighted H index calculation method of adjacent node intensity and side right value, improves node
Discrimination is recognized, makes that it is suitable for the identifications of correlation networks interior joint influence power.
The correlation networks established in step 1 are bidirectional weighting networks, are improved to traditional H index index, simultaneously
Consider the weight and node strength on side in correlation networks.In addition, in the power system, the failure of Targeted Tributary may be to other
Branch causes power out-of-limit, and w is shown as in correlation networksijValue be greater than 1, can increase at this time system occur cascading failure
Risk.Therefore Weighted H index, definition node Weighted H index are defined using counterpart node intensity are as follows:
In formula, WHiIndicate the Weighted H index of node i,Operator, w are calculated for Weighted H indexijExpression is referred to by node i
To the side right value of node j, Sj|iIndicate intensity of the node j relative to node i, SjIndicate the intensity of node j, ΓiIt indicates by node i
The set of all of its neighbor node of direction, α, β indicate regulatory factor；WHiBigger node, corresponding branch are more fragile.
In order to calculate the value of WH, the Weighted H index W H of calculate node i is proposediAlgorithm, as shown in table 1.
1 Weighted H index calculation method of table
Specifically, algorithm can be divided into following steps:
2.1 initialization correlation networks parameters；
2.2 initialization node i Weighted H index values, enable WHi=0, then all of its neighbor node of calculate node i is opposite
Node strength；
2.3 sort all of its neighbor node counterpart node intensity of node i according to sequence from small to large, formation sequence S
={ S1|i,S2|i,…,SM|i, M is the quantity of sequence S；Counting side right value corresponding with sequence S is W={ wi1,wi2,…,wiM}；
Each value w in 2.4 couples of sequence Wik, all in the sequence of calculation to be greater than wikAnd SUMWk, then WHik=min { Sk|i,
SUMWk, traverse all w in sequence WikAfterwards, the Weighted H index W H of node ii=max { WHik|k∈M}。
Utilize the Weighted H index of above-mentioned algorithm calculate node node B and C in weighted network as shown in Figure 3, process
As shown in table 2.As shown in Table 2, it is calculated by Weighted H index, the Weighted H index of node B is max { WHTBi}=3.5, node C
Weighted H index be max { WHTCiThe H index value of }=2.9, two nodes has a marked difference, and shows proposed index
Validity.
2 Weighted H index calculating process of table
In correlation networks, node out-degree indicates influence of the node to other nodes, and node in-degree indicates other sections
Influence of the point to itself.In bidirectional weighting network shown in Fig. 4, Γ1={ 2,3,5,6 }.Therefore in definition node intensity Si
When, we only consider the influence to other nodes.In correlation networks, node out-degree indicates the node to the shadow of other nodes
It rings, reflects the influence power of the node in a network to a certain extent.Node out-degree quantity is more, reflects the shadow of the node
Sound range is wider, and node out-degree weight is bigger, and it is deeper to reflect influence of the node to adjacent node.What formula (3) defined adds
Power H index index just sufficiently combines the depth and range of node influence power in systems, has to node influence power more deep
It portrays with entering, Weighted H index index reflects fragility of former branch of a network during cascading failure.
Step 3: recognizing vulnerable line using Weighted H index
The Weighted H index index obtained according to step 2 is ranked up transmission line of electricity, Weighted H index in correlation networks
Bigger node corresponds to transmission line of electricity that can be more fragile in former power grid；By route Weighted H index index in electric power networks from big
Weighted H index index to minispread, route is bigger, bigger to the influence of system after route is under attack, the mistake load of system
Situation is more serious.
The fragility Attack Research of route can be used to identify to the serious failure of systematic influence, using AC OPA model according to
The sequence of branch number carries out static calculated attack to route, and the system after every route of statistics is attacked is lost load condition, attacked
Process is hit as shown in figure 5, emulating 10000 times, load statistical conditions are lost according to system, calculate VaR (value-at-risk, MW) and CVaR
(risk conditions value, MW) two fragile indexs assess power failure risk；VaR is indicated in the regular period at given confidence level σ
System maximum possible load loss；CVaR indicates conditional average value when loss is more than VaR under given confidence level；In the present invention
σ=0.95 is set.
It is analyzed using IEEE-39 node system as example, topological structure is as shown in fig. 6, the system has 39 sections
Point, 46 branches.The Weighted H index value that every route is calculated according to the method for the present invention, to route according to the big of Weighted H index value
Small carry out descending sort, so that it is determined that the critical circuits of system.If the big route of Weighted H index value is destroyed, just having very much can
It can cause massive blackout accident.
In order to assess the performance of Weighted H index method, table 3 is listed to be recognized according to Weighted H index (α=0.5, β=0.5)
Preceding 5 routes out and the fragile fragility Comparative result for randomly selecting preceding 5 routes.
The vulnerable line recognition result of 3 IEEE-39 node system of table sorts
CompareWithThe two indexes represent the average power failure risk that the transmission line of electricity of most fragile causes；It can be with
See, as caused by most fragile transmission line of electricityWithWeighted H index method is apparently higher than the method for randomly selecting；This shows
Weighted H index method identifies that vulnerable line is accurately and effectively.
In addition, Fig. 7 compares the identification discrimination of Weighted H index He classics H index, as shown in fig. 7, in the range irised out
Interior, classical H index index value remains unchanged, i.e. the fragile degree of these routes is identical, classical these route fragile degrees of H exponent pair
Identification does not have discrimination.On the contrary, Weighted H index index value is successively reduced as the sequence of route increases, to every route
With good discrimination.This demonstrate this patents to the classical improved validity of H index index.
Vulnerable line identification algorithm proposed by the present invention, it is contemplated that the design feature and state characteristic of route, using improvement
H decomposing index method vulnerable line is recognized.Identification result is the fragile link in system, in the process of calculated attack
It is middle that bigger load loss is shown than randomly selected route.In addition, with classical H index contrast, Weighted H index index tool
There is higher identification discrimination.Therefore, this method is to searching electric system vulnerable line, cascading failure blocking strategy, raising
The safety operation level important in inhibiting of system.
Claims (4)
1. a kind of electric system vulnerable line identifying method based on Weighted H index, which comprises the steps of:
Step 1: considering the topological structure feature and operating status characteristic of power system network, establish the second level phase of electric system
Closing property network；
Step 2: considering the weight and node strength on side in correlation networks, classical H index index is improved, is weighted
H index index；
Step 3: the Weighted H exponent pair transmission line of electricity obtained according to step 2 is ranked up, and completes the identification of vulnerable line.
2. a kind of electric system vulnerable line identifying method based on Weighted H index according to claim 1, feature exist
In the construction method of the second level correlation networks of electric system in the step 1 are as follows:
1.1 calculate electric system benchmark trend, record the Capacity Margin M of each routej；
1.2 using N-1 Load flow calculation as foundation, successively cut-offs every branch in power grid, with other branches caused after branch breaking
Power flow increment be side right obtain a power increment matrix Δ P；
1.3 to determine whether branch power out-of-limit, if nothing, is transferred to step 1.4；Otherwise, retain out-of-limit branch pair in matrix Δ P
Then the element value answered cut-offs out-of-limit branch, again computing system trend, update power increment square according to second of power flow increment
Battle array Δ P；
1.4 by each element in power increment matrix Δ P divided by the Capacity Margin of corresponding branch, obtain improved correlation
Matrix R, specifically:
Wherein Δ rijIt indicates that route i's cut-offs the influence caused by route j, is calculated by following formula:
M in formulajIndicate the Capacity Margin of route j, Δ PijIndicate that the power increment after route i is cut-off to route j, n indicate system
Middle route sum, in the case where not considering transmission line of electricity to itself affect, all diagonal elements are set as 0 in correlation matrix R；
Then using grid branch as node, the element in matrix R is side right value, constructs a new network, as the two of electric system
Grade correlation networks.
3. a kind of electric system vulnerable line identifying method based on Weighted H index according to claim 1, feature exist
In the step 2 specifically: define Weighted H index, definition node Weighted H index using counterpart node intensity are as follows:
In formula, WHiIndicate the Weighted H index of node i,Operator, w are calculated for Weighted H indexijIt indicates to be directed toward node by node i
The side right value of j, Sj|iIndicate intensity of the node j relative to node i, SjIndicate the intensity of node j, ΓiWhat expression was directed toward by node i
The set of all of its neighbor node, α, β indicate regulatory factor；WHiBigger node, corresponding branch are more fragile；
The Weighted H index W H of calculate node iiAlgorithm specifically:
2.1 initialization correlation networks parameters；
2.2 initialization node i Weighted H index values, enable WHi=0, the then counterpart node of all of its neighbor node of calculate node i
Intensity；
2.3 sort all of its neighbor node counterpart node intensity of node i according to sequence from small to large, formation sequence S=
{S1|i,S2|i,…,SM|i, M is the quantity of sequence S；Counting side right value corresponding with sequence S is W={ wi1,wi2,…,wiM}；
Each value w in 2.4 couples of sequence Wik, all in the sequence of calculation to be greater than wikAnd SUMWk, then WHik=min { Sk|i,
SUMWk, traverse all w in sequence WikAfterwards, the Weighted H index W H of node ii=max { WHik|k∈M}。
4. a kind of electric system vulnerable line identifying method based on Weighted H index according to claim 1, feature exist
In, the step 3 specifically, in calculate node system topology every route Weighted H index, to route according to Weighted H
The size of index carries out descending sort, so that it is determined that the vulnerable line of electric system.
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| CN111313408B (en) * | 2020-03-05 | 2022-04-29 | 西南交通大学 | Power grid fragile line identification method considering transient energy correlation |
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| CN112615365A (en) * | 2020-12-08 | 2021-04-06 | 国网四川省电力公司经济技术研究院 | Smart power grid vulnerability key point identification method and device |
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